






"""simple docstring"""
from __future__ import annotations

# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
snake_case : str     		=		1_0


def 							A						(				__snake_case: int ,     __snake_case: int ,     __snake_case: list[int] ,     __snake_case: int  )    ->		int:

       """simple docstring"""





       for i in range(__snake_case ,     __snake_case  ):
              if array[i] == target:
                     return i
       return -1


def 							A						(				__snake_case: list[int] ,     __snake_case: int  )    ->		int:

       """simple docstring"""





       __magic_name__      				=    0
       __magic_name__      				=    len(__snake_case  )
       while left <= right:
              if right - left < precision:
                     return lin_search(__snake_case ,     __snake_case ,     __snake_case ,     __snake_case  )

              __magic_name__      				=    (left + right) // 3 + 1
              __magic_name__      				=    2 * (left + right) // 3 + 1

              if array[one_third] == target:
                     return one_third
              elif array[two_third] == target:
                     return two_third

              elif target < array[one_third]:
                     __magic_name__      				=    one_third - 1
              elif array[two_third] < target:
                     __magic_name__      				=    two_third + 1

              else:
                     __magic_name__      				=    one_third + 1
                     __magic_name__      				=    two_third - 1
       else:
              return -1


def 							A						(				__snake_case: int ,     __snake_case: int ,     __snake_case: list[int] ,     __snake_case: int  )    ->		int:

       """simple docstring"""





       if left < right:
              if right - left < precision:
                     return lin_search(__snake_case ,     __snake_case ,     __snake_case ,     __snake_case  )
              __magic_name__      				=    (left + right) // 3 + 1
              __magic_name__      				=    2 * (left + right) // 3 + 1

              if array[one_third] == target:
                     return one_third
              elif array[two_third] == target:
                     return two_third

              elif target < array[one_third]:
                     return rec_ternary_search(__snake_case ,     one_third - 1 ,     __snake_case ,     __snake_case  )
              elif array[two_third] < target:
                     return rec_ternary_search(two_third + 1 ,     __snake_case ,     __snake_case ,     __snake_case  )
              else:
                     return rec_ternary_search(one_third + 1 ,     two_third - 1 ,     __snake_case ,     __snake_case  )
       else:
              return -1


if __name__ == "__main__":
 import doctest

 doctest.testmod()

 snake_case : List[str]     		=		input("""Enter numbers separated by comma:\n""").strip()
 snake_case : List[str]     		=		[int(item.strip()) for item in user_input.split(""",""")]
 assert collection == sorted(collection), f"List must be ordered.\n{collection}."
 snake_case : Any     		=		int(input("""Enter the number to be found in the list:\n""").strip())
 snake_case : Union[str, Any]     		=		ite_ternary_search(collection, target)
 snake_case : str     		=		rec_ternary_search(0, len(collection) - 1, collection, target)
 if resulta != -1:
  print(f"""Iterative search: {target} found at positions: {resulta}""")
  print(f"""Recursive search: {target} found at positions: {resulta}""")
 else:
  print("""Not found""")







"""simple docstring"""
from datetime import datetime

import matplotlib.pyplot as plt
import torch


def 							A						(				__snake_case: Optional[int]  )    ->		Tuple:

       """simple docstring"""





       for param in module.parameters():
              __magic_name__      				=    False


def 							A						(				)    ->		Optional[Any]:

       """simple docstring"""





       __magic_name__      				=    'cuda' if torch.cuda.is_available() else 'cpu'
       if torch.backends.mps.is_available() and torch.backends.mps.is_built():
              __magic_name__      				=    'mps'
       if device == "mps":
              print(
                  'WARNING: MPS currently doesn\'t seem to work, and messes up backpropagation without any visible torch'
                  ' errors. I recommend using CUDA on a colab notebook or CPU instead if you\'re facing inexplicable issues'
                  ' with generations.'  )
       return device


def 							A						(				__snake_case: int  )    ->		List[Any]:

       """simple docstring"""





       __magic_name__      				=    plt.imshow(__snake_case  )
       fig.axes.get_xaxis().set_visible(__snake_case  )
       fig.axes.get_yaxis().set_visible(__snake_case  )
       plt.show()






def 							A						(				)    ->		List[Any]:

       """simple docstring"""





       __magic_name__      				=    datetime.now()
       __magic_name__      				=    current_time.strftime('%H:%M:%S'  )
       return timestamp